Deep Learning Techniques for IoT Security and Privacy

1. Auflage 2022
ISBN: 978-3-030-89024-7
Verlag: Springer International Publishing

Buch, Englisch, Band 997, 257 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 588 g

Reihe: Studies in Computational Intelligence

This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.

Zielgruppe

Research

Autoren/Hrsg.

Abdel-Basset, Mohamed

Ding, Weiping

Moustafa, Nour

Hawash, Hossam

Fachgebiete

• Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Chapter 1, Conceptualization of Security, Forensics, and Privacy of Internet of Things.- Chapter 2, Internet of Things, Preliminaries and Foundations.- Chapter 3, Internet of Things Security Requirements, Threats, Countermeasures.- Chapter 4, Digital Forensics in Internet of Things.- Chapter 5, Supervised Deep Learning for Secure Internet of Things.- Chapter 6, Unsupervised Deep Learning for Secure Internet of Things.- Chapter 7, Semi-supervised Deep Learning for Secure Internet of Things.- Chapter 8, Reinforcement Learning for Secure Internet of Things.- Chapter 9, Federated Learning for Privacy-Preserving Internet of Things.- Chapter 10, Challenges, Opportunities, and Future Prospects.